Voice enhancement method based on DNN noise classification

A technology of speech enhancement and noise classification, applied in speech analysis, speech recognition, instruments, etc., can solve the problems of lower recognition rate, failure to meet practical applications, and deterioration of effects, and achieve the effect of improving the quality of speech enhancement

Pending Publication Date: 2019-04-02
沈阳品尚科技有限公司
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AI Technical Summary

Problems solved by technology

The interference of background noise deteriorates the performance of speech signal processing, such as speech coding, speech synthesis, speech recognition, etc.
For example, speech recognition is a key step in human-computer interaction using spe

Method used

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  • Voice enhancement method based on DNN noise classification
  • Voice enhancement method based on DNN noise classification
  • Voice enhancement method based on DNN noise classification

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Embodiment Construction

[0026] Below in conjunction with accompanying drawing and embodiment, the specific embodiment of the present invention will be described in further detail. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0027] A speech enhancement method based on DNN noise classification, such as figure 2 shown, including the following steps:

[0028] Step 1, preprocess the noise signal by means, standardization, pre-emphasis, and frame-by-frame windowing, and add a window in the voice activity detection module of the voice processing system to determine the non-speech segment signal; then perform fast processing on each frame of voice signal Fourier transform and calculate the spectral line energy; make the spectrum of the speech signal pass through the Mel filter bank, and multiply the spectral energy by the frequency response H of the Mel filter m (k) to obtain the Mel filter energy, as shown in the...

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Abstract

The invention provides a voice enhancement method based on DNN noise classification, and relates to the technical field of voice recognition. The method comprises the following steps: carrying out preprocessing on noise signals, and determining signals of the non-voice segment; for each frame of voice signals, carrying out fast Fourier transform, and calculating the spectral line energy; enablingthe frequency spectrum of the voice signals to pass through a Mel filter group, multiplying the frequency spectrum energy with the frequency response of the Mel filters, thus obtaining the Mel filtering energy; carrying out discrete cosine transform on the logarithm of the Mel filtering energy of each frame of signals, thus obtaining a Mel cepstrum parameter which serves as the feature vector of each frame of Mel filtering of the voice; taking the feature vector of each frame of Mel filtering as a 24-dimensional vector, and also as the input of the deep neural network; and carrying out training and classifying on the noises by utilizing the deep neural network. For the voice enhancement method based on DNN noise classification, through the classification for noises, the subsequent voice enhancement quality is obviously improved in the subjective/object testing.

Description

technical field [0001] The invention relates to the technical field of speech recognition, in particular to a speech enhancement method based on DNN noise classification. Background technique [0002] Speech enhancement is a technology that extracts useful speech signals from background noise, and suppresses and reduces noise interference after speech signals are interfered by various noises. Speech enhancement is an effective method to solve the noise pollution of speech signals. It is also a key link and step in speech signal processing, and is widely used in people's production and life. The interference of background noise deteriorates the performance of speech signal processing, such as speech coding, speech synthesis, and speech recognition. For example, speech recognition is a key step in human-computer interaction using speech signals. The existing speech recognition system has a high recognition rate in a quiet environment, but in a strong noise environment, the r...

Claims

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Application Information

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IPC IPC(8): G10L21/02G10L25/30G10L25/24G10L15/16G10L15/06G10L25/18
CPCG10L15/063G10L15/16G10L21/02G10L25/18G10L25/24G10L25/30
Inventor 高天寒陈爽
Owner 沈阳品尚科技有限公司
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